Services

DevOps is an emerging model of product delivery that facilitates higher and faster rates of change through the optimisation of development and delivery processes. [...]
As the Fourth Industrial Revolution presses upon us all, we and many in our industry believe successful Digital Transformation initiatives will need DevOps to be the driving force.

I'm here to assist you to tackle the challenges of the Digital Transformation. No matter if it's migrating an existing Software stack to a new System Architecture or platform,
or building a new service from the ground up. I offer a decade of experience in Dev and Ops combined with a battle proven stack of services to build next generation infrastructure.

References

Design and implementation of container infrastructure based on Docker and Kubernetes. Design and implementation of CI/CD processes based on GitLab. Design and implementation of a metrics monitoring system based on Prometheus. Training and support of ~60 developers and ~15 ops employees.

Design and implementation of a RESTful web service as API for an ETL pipeline and several web front-ends. The web service was implemented in Python with the connexion library and Flask. The API reflected a rather complex domain model with tight security requirements.

Design and implementation of a ETL pipeline in Python Luigi to clean and transform several data sources for big-data analysis. ETL jobs were executed in Docker containers.

PythonLuigiPostgreSQLDocker

Docker TrainingYear: 2017, Several customers, Role: Trainer

Two day training program for Docker and several Docker tools. Goal of the training was to bring people with Dev or Ops background and little Docker knowledge up to speed. Training included a deep dive into the Docker technology stack and hands on sessions with real projects of the teams.

Concept and implementation of a fully automated container based CI/CD cloud infrastructure. Goal of the project was to implement processes and tools to enable the existing team to deploy and operate their SaaS product fully automated and tightly integrated with AWS.

Concept and setup of a Slack like Chat Service offered as SaaS. The project had reliability as well as performance goals. AWS EC2 and Private Cloud infrastructure mix. Service and container orchestration was done with SaltStack. Several loadbalanced web applications and a MongoDB cluster in a multi datacenter setup. Services operated in a Docker overlay network provided by flannel clustered through etcd.

Concept and POC for a container based Distributed Task Queue to manage workflows. The Distributed Task Queue was implemented in Python using Celery. Services provided via Docker containers. RabbitMQ used as AMQP provider for Celery and ElasticSearch for event logging.

API driven database to historical store billions of IP blacklistings across several blacklist providers through a multi dimensional key design for highly effective range queries to provide an aggregated
blacklist service for network operators.

Blog

kubernetes

This article is about using containerd 1.1 directly with Kubernetes instead of Docker. Since 2008 with the first release of LXC and the release of Docker in 2013 a lot has happened in Linux container...

ubuntu

Kubernetes supports the container engine Docker only up to a specific version (currently 17.03). For that it needs to be ensured that apt wouldn’t update Docker to any unsupported version. The base installation of Docker...

python

Just finished integrating Azure ActiveDirectory OAuth2 with a Python Web API using the following authentication scenario. The JWT token is requested through a web application and passed to the Web API for resource access. The...

tools

Recently I was annoyed by typing in my credentials for Git HTTP/HTTPS auth all the time. On my search for a solution I found the credential.helper. With the git-credential-cache Git will cache your credentials for...

python

In my last performance comparison I compared libraries with non performance goals with datetime and udatetime, to illustrate the impact of your library choice. Arrow, Pendulum and Delorean are awesome choices when it comes to...

python

The big alternatives to Python datetime all share similar goals. These goals are ease of use, simplicity and intelligent/user friendly API design. Awesome goals and I love those libraries for investing a lot of effort...

python

I just finished the performance optimized pure Python implementation of my RFC3339 date-time library udatetime for PyPy and Python 3.5. The benchmark say PyPy is now officially the fastest with udatetime. Again it’s astonishing how...

python

Working with date-time formats can be pretty upsetting because of the variate of different formats people can come up with. date-times are used everywhere not just only logging or meta data in database entries and...